This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

A rigorous but practical introduction to the economic, financial, and political principles underlying commodity markets. Commodities have become one of the fastest growing asset classes of the last decade and the object of increasing attention from investors, scholars, and policy makers. Yet existing treatments of the topic are either too theoretical, ignoring practical realities, or largely narrative and nonrigorous. This book bridges the gap, striking a balance between theory and practice. It offers a solid foundation in the economic, financial, and political principles underlying commodities markets. The book, which grows out of courses taught by the author at Columbia and Johns Hopkins, can be used by graduate students in economics, finance, and public policy, or as a conceptual reference for practitioners. After an introduction to basic concepts and a review of the various types of commodities—energy, metals, agricultural products—the book delves into the economic and financial dynamics of commodity markets, with a particular focus on energy. The text covers fundamental demand and supply for resources, the mechanics behind commodity financial markets, and how they motivate investment decisions around both physical and financial portfolio exposure to commodities, and the evolving political and regulatory landscape for commodity markets. Additional special topics include geopolitics, financial regulation, and electricity markets. The book is divided into thematic modules that progress in complexity. Text boxes offer additional, related material, and numerous charts and graphs provide further insight into important concepts.

Neil Grigg presents the core issues of economics and finance that relate directly to the work of civil engineers, construction managers, and public works and utility officials.

For professional and individual investors, executives or business students, a unique atlas of what makes the markets move.

This book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers decomposition methods, autocorrelation methods for univariate time series, volatility and duration modeling for financial time series, and multivariate time series methods, such as cointegration and recursive state space modeling. It also includes numerous practical examples to demonstrate the theory using real-world data, as well as exercises at the end of each chapter to aid understanding. This book serves as a reference text for researchers, students and practitioners interested in time series, and can also be used for university courses on econometrics or computational finance.

An authoritative guide to the new economics of our crisis-filled century. Published in collaboration with the Institute for New Economic Thinking. The 2008 financial crisis was a seismic event that laid bare how financial institutions’ instabilities can have devastating effects on societies and economies. COVID-19 brought similar financial devastation at the beginning of 2020 and once more massive interventions by central banks were needed to heed off the collapse of the financial system. All of which begs the question: why is our financial system so fragile and vulnerable that it needs government support so often? For a generation of economists who have risen to prominence since 2008, these events have defined not only how they view financial instability, but financial markets more broadly. Leveraged brings together these voices to take stock of what we have learned about the costs and causes of financial fragility and to offer a new canonical framework for understanding it. Their message: the origins of financial instability in modern economies run deeper than the technical debates around banking regulation, countercyclical capital buffers, or living wills for financial institutions. Leveraged offers a fundamentally new picture of how financial institutions and societies coexist, for better or worse. The essays here mark a new starting point for research in financial economics. As we muddle through the effects of a second financial crisis in this young century, Leveraged provides a road map and a research agenda for the future.

Mathematics has become indispensable in the modelling of economics, finance, business and management. Without expecting any particular background of the reader, this book covers the following mathematical topics, with frequent reference to applications in economics and finance: functions, graphs and equations, recurrences (difference equations), differentiation, exponentials and logarithms, optimisation, partial differentiation, optimisation in several variables, vectors and matrices, linear equations, Lagrange multipliers, integration, first-order and second-order differential equations. The stress is on the relation of maths to economics, and this is illustrated with copious examples and exercises to foster depth of understanding. Each chapter has three parts: the main text, a section of further worked examples and a summary of the chapter together with a selection of problems for the reader to attempt. For students of economics, mathematics, or both, this book provides an introduction to mathematical methods in economics and finance that will be welcomed for its clarity and breadth.